Measuring improvement in dyspnoea: should absolute or relative values be used?
2014
To the Editor:
The same patient outcome data from clinical trial results, when presented as absolute or relative changes, may appear different in magnitude. Recommendations are to report both absolute and relative, or at least baseline, data from which to calculate absolute values [1, 2]. A systematic review of efficacy trials demonstrated that only relative values were reported in most study abstracts (88%) and the main text (75%) [3].
To inform clinical practice, outcome improvements, whether relative or absolute, must be statistically significant and clinically meaningful. A minimal clinically important difference (MCID) should inform sample size calculations for clinical trials.
Two main methods identify an MCID (distribution and anchor-based methods); ideally used together to interpret one in the context of the other [4]. The distribution method is a statistical calculation based on the baseline variability of the measure in the population studied. This gives an effect size (change after intervention divided by standard deviation of baseline scores), the magnitude of which relates to a small, moderate or large clinical effect [5]. Thus the distribution method can only be used to calculate an absolute MCID as there is no standard deviation of baseline score for a relative measure.
The anchor-based method relates the change in score
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